[1] Shi W, Li N, Chu C. C, Gadh R. Real-time energy management in microgrids. IEEE Transactions on Smart Grid. 2015; 8(1): 228-238.10.1109/TSG.2015.2462294
[2] Li B, Roche R, Miraoui A. Microgrid sizing with combined evolutionary algorithm and MILP unit commitment. Applied energy. 2017; 188: 547-562. https://doi.org/10.1016/j.apenergy.2016.12.038
[3] Kumar D, Verma Y. P, Khanna R. Demand response-based dynamic dispatch of microgrid system in hybrid electricity market. International Journal of Energy Sector Management. 2019; 13(2): 318-340. https://doi.org/10.1108/IJESM-12-2017-0008
[4] Hussain A, Bui V. H, Kim H. M. Microgrids as a resilience resource and strategies used by microgrids for enhancing resilience. Applied energy. 2019; 240: 56-72. https://doi.org/10.1016/j.apenergy.2019.02.055
[5] Xu D, Long Y. The impact of government subsidy on renewable microgrid investment considering double externalities. Sustainability. 2019;11(11): 3168. https://doi.org/10.3390/su11113168
[6] Philipo G H, Chande Jande Y A, Kivevele T. Demand‐side management of solar microgrid operation: Effect of time‐of‐use pricing and incentives. Journal of Renewable Energy. 2020; (1); 6956214. https://doi.org/10.1155/2020/6956214
[7] Rajamand S. Cost reduction in microgrid using demand response program of loads and uncertainty modeling with point estimation method. International transactions on electrical energy systems. 2020; 30(4): e12299. https://doi.org/10.1002/2050-7038.12299
[8] Kumar P S, Chandrasena R P. S., Ramu V, Srinivas G, Babu K. V. S. M. Energy management system for small scale hybrid wind solar battery based microgrid. IEEE access. 2020; 8: 8336-8345. https://doi.org/10.1109/ACCESS.2020.2964052
[9] Luo L, Abdulkareem S. S, Rezvani A, Miveh M. R, Samad S, Aljojo N., Pazhoohesh M. Optimal scheduling of a renewable based microgrid considering photovoltaic system and battery energy storage under uncertainty. Journal of Energy Storage. 2020; 28: 101306. https://doi.org/10.1016/j.est.2020.101306
[10] Chandak S, Rout P. K. The implementation framework of a microgrid: A review. International Journal of Energy Research. 2021; 45(3): 3523-3547. https://doi.org/10.1002/er.6064
[11] Li R, Leung G. C. The relationship between energy prices, economic growth and renewable energy consumption: Evidence from Europe. Energy Reports. 2021; 7: 1712-1719. https://doi.org/10.1016/j.egyr.2021.03.030
[12] Tsao Y C, Linh, V. T. A new three-part tariff pricing scheme for the electricity microgrid considering consumer regret. Energy. 2022; 254: 124387. https://doi.org/10.1016/j.energy.2022.124387
[13] Qu D, Li J, Yong M. Real-time pricing for smart grid considering energy complementarity of a microgrid interacting with the large grid. International Journal of Electrical Power & Energy Systems. 2022; 141: 108217. https://doi.org/10.1016/j.ijepes.2022.108217
[14] Hosan S, Rahman M M, Karmaker S C, Saha B. B. Energy subsidies and energy technology innovation: Policies for polygeneration systems diffusion. Energy. 2023; 267: 126601.
[15] Li B, Zhao R, Lu J., Xin, K, Huang J, Lin G, Pang X. Energy management method for microgrids based on improved Stackelberg game real-time pricing model. Energy Reports. 2023; 9:1247-1257.
[16] Jabari F, Zeraati M, Sheibani M, Arasteh H. Robust self-scheduling of pvs-wind-diesel power generation units in a standalone microgrid under uncertain electricity prices. Journal of Operation and Automation in Power Engineering. 2024; 12(2): 152-162. https://doi.org/10.22098/joape.2023.11096.1829
[17] Du J, Han X, Wang J. Distributed cooperation optimization of multi-microgrids under grid tariff uncertainty: A nash bargaining game approach with cheating behaviors. International Journal of Electrical Power & Energy Systems. 2024; 155: 109644. https://doi.org/10.1016/j.ijepes.2023.109644
[18] Xu, W., Lin, F., Jia, R., Tang, C., Zheng, Z., & Li, M. Game-Based Pricing for Joint Carbon and Electricity Trading in Microgrids. IEEE Internet of Things Journal. 2024. https://doi.org/10.1109/JIOT.2024.3400392
[19] Leclere J, Wang J, Bian J. Joint production and energy supply planning of an industrial microgrid. Applied Energy. 2024; 315: 119034. https://doi.org/10.1007/s12667-023-00645-5
[20] Nojavan M, Maghouli P. A Novel Dynamic Pricing Time‐Based Demand Response Program for Net‐Load Flexibility of Microgrids. International Journal of Energy Research. 2024; (1): 2104716. https://doi.org/10.1155/2024/2104716
[21] Kumar A, Kiran D, Padhy N. P. Pricing strategy for local power-sharing between distribution network and microgrid operators. International Journal of Electrical Power & Energy Systems. 2024; 157: 109820. https://doi.org/10.1016/j.ijepes.2024.109820
[22] Zhang Z, Huang Y, Chen Z, Lee W.-J. Integrated demand response for microgrids with incentive-compatible bidding mechanism. IEEE Transactions on Industry Applications. 2022; 58(5): 5612–5624. https://doi.org/10.1109/TIA.2022.3154789
[23] Li Y, Chen X. Dynamic energy pricing strategies in local electricity markets under renewable integration. Applied Energy. 2023; 341: 121048. https://doi.org/10.1016/j.apenergy.2023.121048
[24] Wang J, Liu H, Zhao M. Multi-level game models for government subsidy allocation in renewable energy microgrids. Energy Policy. 2024; 185: 113525. https://doi.org/10.1016/j.enpol.2024.113525
[25] Hosseini S, Karimi A, Dehghan M. Adaptive policy design for renewable microgrids under demand uncertainty. Renewable Energy. 2023; 209; 134–146. https://doi.org/10.1016/j.renene.2023.04.027
[26] Khalili R, Xu Q. Stochastic optimization of renewable microgrid operations under uncertain demand and generation. Energy Reports. 2022; 8: 10567–10581. https://doi.org/10.1016/j.egyr.2022.09.018